The development of the World Wide Web (the “Web”), web search engines, and social networking services has resulted in the generation and collection of vast quantities of information. Such information is often presented to Web users through a number of websites that display the information on substantially static or slowly evolving Web pages and update those Web pages at various intervals (e.g., weekly, daily, hourly). Examples of such static data sources include numerous newspaper websites, news network websites, magazine publisher websites, industry press websites, etc. However, while some Web pages are updated by their publishers more frequently than others, the sources and frequency of such updates are typically limited (e.g., an editor posts a new article on the Web page one or twice a day).
On the other hand, a vast amount of online information is also generated and presented through dynamic data sources, including without limitation various RSS feeds, blogs, micro-blogs, forums, chat rooms, etc., which tend to provide information of a more current, asynchronous, and rapidly changing nature. For example, a blogger may post an article on his or her blog at the beginning of the day and then, throughout the day and into the future, others are posting comments to the article in the article's comments section. In addition, dynamic data sources often provide such information automatically or semi-automatically as the information is published by various authors, commenters, and information services, rather than merely being posted manually to a static Web page by an editor on a periodic basis. For example, online comments and discussions about a snowstorm, uploaded images and videos of the snowstorm, etc. are automatically aggregated and re-published frequently through various social media channels in the hours before, during and after the snowstorm. In contrast, static Web pages, such as pages on a website for the city experiencing the snowstorm, tend not to capture in near-real-time the surge of interest about the snow storm that is captured by the dynamic data sources.
Furthermore, the relevancy of information to users may diminish quickly as the subject matter becomes less current. For example, user interest about the snowstorm information wanes after the snowstorm has ended, and as such, if such information were captured on static Web pages, the relevance of the information from static data sources to users will also diminish over time. In contrast, the temporally-less-relevant information from dynamic data sources typically gives way to new information about more relevant topics as time progresses. Accordingly, information generated by such dynamic, or “trending,” data sources tends to appear and then recede into the background very quickly so that the most relevant information is more prominent and readily accessible. Thus, dynamic data sources provide a relevancy advantage over substantially unchanging and stale static data sources.